When Algorithms Amplify Division: Lessons from Charlie Kirk’s Death
As more details of the assassination of conservative activist Charlie Kirk at Utah Valley University emerge, including details from the social media feeds of 22-year-old Tyler Robinson, charged with aggravated murder, the online reaction nationally and globally already shows something bigger.
Social feeds don’t just reflect what individuals feel; they steer it.
Within minutes of the news following the shooting, social feeds split into mirrored worlds: tributes and anger in one, taunts and conspiracy in another.
Modern feeds on Facebook, Instagram, YouTube, TikTok, and X are ranked by machine-learning systems that predict what will keep participants engaged. The inputs are mostly behavioral: watch time, dwell time, clicks, shares, replies, “rewatches,” and occasionally satisfaction.
Because platforms chase engagement, the most intense content tends to spread more widely. That’s the logic behind engagement-based feeds. A study from the Knight First Amendment Institute at Columbia University shows that these systems often amplify posts that stir anger, especially toward people with different beliefs or values.
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